Cloud/Kubernetes Platform Engineer, AWS Lead Software Engineer

About the role

As a Lead Software Engineer within the Commercial and Investment Bank Equities group at JPMorganChase, you will be an integral part of an agile team enhancing, building, and delivering trusted market-leading technology products in a secure, stable, and scalable way. You will serve as a core technical contributor, driving critical technology solutions across multiple technical areas to support the firm's business objectives.

Responsibilities

• Cloud Platform & Infrastructure as Code: Design and implement AWS cloud infrastructure using Terraform and/or CloudFormation, emphasizing reusable modules, environment promotion, and automation. Build standardized platform components (networking, IAM patterns, EKS add-ons, observability integration) for consistent adoption.
• Kubernetes EKS (Core Focus): Provision, upgrade, and operate EKS clusters end-to-end (cluster lifecycle, node groups, autoscaling, cluster add-ons). Implement and support Kubernetes primitives: Deployments, StatefulSets, Services, Ingress, ConfigMaps, Secrets, namespaces, RBAC, requests/limits, PDBs, HPA, VPA, taints/tolerations, affinity, anti-affinity. Troubleshoot cluster and workload issues to improve reliability.
• Security, Identity, and Secrets: Enforce least-privilege IAM and workload identity patterns (including IRSA for EKS). Manage secrets using cloud-native services and Kubernetes patterns, ensuring secure access and rotation practices. Apply security best practices across cloud and Kubernetes (network segmentation, encryption, secure configuration).
• CI/CD & Release Enablement: Build and maintain CI/CD pipelines (e.g., Jenkins/Jules or similar) to support reliable application delivery. Collaborate with developers to improve build/deploy workflows and support release processes.
• Observability & Incident Response: Monitor infrastructure health using cloud-native monitoring and observability platforms (metrics, logs, alerting). Participate in incident response, including log analysis, troubleshooting, and automation for faster containment and remediation. Produce and maintain runbooks and operational documentation.
• QA & Performance Testing: Partner with application teams to perform end-to-end testing aligned with business requirements. Execute stress performance testing in lower environments and establish capacity expectations and scaling approaches.
• Drive team adoption of enterprise-authorized AI-assisted engineering practices to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review, refactoring, test strategy acceleration, incident root-cause analysis). Establish consistent validation standards (secure coding, peer review, automated testing) and promote reuse of effective patterns.
• Apply knowledge of tools within the Software Development Life Cycle toolchain, including AI-assisted development and automation, to enhance the value realized by automation.
• Identify opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability.
• Lead evaluation sessions with external vendors, startups, and internal teams to assess architectural designs, technical credentials, and applicability for existing systems.

Requirements

• Formal training or certification on software engineering concepts and 5+ years of applied experience.
• Hands-on practical experience in system design, application development, testing, and operational stability.
• Advanced proficiency in one or more programming languages (e.g., Python, Bash, PowerShell, Go).
• Strong experience with AWS, Azure, or GCP, with a preference for AWS.
• Strong experience with Kubernetes, ideally EKS in production.
• Proficiency with Infrastructure as Code (Terraform and/or CloudFormation).
• Strong networking fundamentals: VPCs, VNets, subnets, routing, load balancers, security groups/NSGs.
• Experience with Docker and containerized workloads.
• Solid understanding of IAM, encryption, secrets, and cloud security best practices.
• Demonstrated experience leading effective use of approved AI-assisted software development tools (e.g., for coding, code review, test acceleration, troubleshooting). Ability to set team expectations for validating AI outputs for correctness, performance, and security.
• Strong understanding of responsible AI use in engineering workflows, including data sensitivity, secure handling of inputs/outputs, and adherence to resiliency and security expectations. Experience coaching engineers on safe, compliant adoption.
• Proficient in all aspects of the Software Development Life Cycle.

Preferred Qualifications

• Multi-cloud experience.
• Background in security engineering or DevSecOps.
• Exposure to kdb+/q environments (helpful but not required) and ability to assist in troubleshooting/log analysis.

Benefits

• Competitive total rewards package, including base salary determined by role, experience, skill set, and location.
• Commission-based pay and/or discretionary incentive compensation for eligible roles, awarded in cash and/or forfeitable equity.
• Comprehensive health care coverage.
• On-site health and wellness centers.
• Retirement savings plan.
• Backup childcare.
• Tuition reimbursement.
• Mental health support and financial coaching.